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Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks
(Hindawi, 2012)
[Abstract] The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has ...
Optimization of NIR Calibration Models for Multiple Processes in the Sugar Industry
(Elsevier, 2016-10-14)
[Abstract] The measurements of Near-Infrared (NIR) Spectroscopy, combined with data analysis techniques, are widely used for quality control in food production processes.
This paper presents a methodology to optimize ...
Automatic multiscale vascular image segmentation algorithm for coronary angiography
(Elsevier, 2018-09)
[Abstract] Cardiovascular diseases, particularly severe stenosis, are the main cause of death in the western world. The primary method of diagnosis, considered to be the standard in the detection and quantification of ...
S2SNet: a tool for transforming characters and numeric sequences into star network topological indices in chemoinformatics, bioinformatics, biomedical, and social-legal sciences
(Bentham, 2013)
[Abstract] The study of complex systems such as proteins/DNA/RNA or dynamics of tax law systems can be carried out with the complex network theory. This allows the numerical quantification of the significant information ...
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
(Springer Nature, 2019-06-26)
[Abstract]
Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ...
BiOSS: A system for biomedical ontology selection
(Elsevier Ireland Ltd, 2014-04)
In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing ...
UAV Swarm Path Planning With Reinforcement Learning for Field Prospecting
(Springer, 2022-03-03)
[Abstract] There has been steady growth in the adoption of Unmanned Aerial Vehicle (UAV) swarms by operators due to their time and cost benefits. However, this kind of system faces an important problem, which is the ...
Detection of Bovine Mastitis in Raw Milk, Using a Low-Cost NIR Spectrometer and k-NN Algorithm
(MDPI, 2021)
[Abstract] Among the bovine diseases, mastitis causes high economic losses in the dairy production system. Nowadays, detection under field conditions is mainly performed by the California Mastitis Test, which is considered ...
DoME: A Deterministic Technique for Equation Development and Symbolic Regression
(Elsevier, 2022-03-04)
[Abstract] Based on a solid mathematical background, this paper proposes a method for Symbolic Regression that enables the extraction of mathematical expressions from a dataset. Contrary to other approaches, such as Genetic ...
Prediction of Breast Cancer Proteins Involved in Immunotherapy, Metastasis, and RNA-Binding Using Molecular Descriptors and Artifcial Neural Networks
(Springer Nature, 2020-05-22)
[Abstract]
Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression
deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental
determinants are involved. ...